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About 10,000 papers for “dynamic programming algorithm”

Dynamic Programming algorithm for optimal control of Tidal Range Schemes

Reza Ahmadian, Man Yue Lam, Yuxuan Liu (15110048) · Cardiff University · 2026

Optimising the operation and design of tidal range schemes is a long standing and critical problem in their design which also affects their financial feasibility. The optimisation process is very time consuming considering its complexity and the number of variables which leads to significant simplifications in the process. Enhancing the efficiency and accuracy of optimisation methods is essential for maximising their energy output. This dataset includes underpinning data which support the approach we propose an efficient tabular dynamic programming for tidal range scheme optimisation by refining the algorithm. Dynamic programming is capable of finding the global optimal solution given that the assumptions used to formulate the optimisation problem are valid. The algorithm refined in this study was tested with two different schemes, namely the West Somerset Lagoon and the North Wales Lagoon in the UK, and demonstrated accurate and efficient prediction of the scheme’s operation. The computational time required by the dynamic programming algorithm was significantly lower than the most promising optimisation approaches used for tidal range schemes, namely Genetic Algorithm, showing potential for real time application. The refined algorithm includes provisions to simulate tidal range schemes with block formulation to account for the fact that turbines and sluice gates are usually installed in different blocks and are subjected to tidal phase differences. Results demonstrate that optimisation including the multi block formulation lead to electricity generation up to 6% more annually. NWL in the file names refer to North Wales Lagoon and WSL refers to West Somerset Lagoon.

Cited by 0Open access

The 'orthogonal algorithm' for optical flow detection using dynamic programming

Georges Quénot · 1992

An algorithm for optical flow detection is introduced. It is based on an iterative search for a displacement field that minimizes the L/sub 1/ or L/sub 2/ distance between two images. Both changes are sliced into parallel and overlapping strips. Corresponding strips are aligned using dynamic programming. Two passes are performed using orthogonal slicing directions. This process is iterated in a pyramidal fashion by reducing the spacing and width of the strips. This algorithm provides very-high-quality matching for calibrated patterns as well as for human visual sensation. The results appear to be at least as good as those obtained with classical optical flow detection methods.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 37

A dynamic programming algorithm for RNA structure prediction including pseudoknots

Elena Rivas, Sean R. Eddy · arXiv (Cornell University) · 1998

We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of ${\cal O}(N^6)$ in time and ${\cal O}(N^4)$ in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the algorithm that generates the optimal minimum energy structure for a single RNA sequence, using standard RNA folding thermodynamic parameters augmented by a few parameters describing the thermodynamic stability of pseudoknots. We demonstrate the properties of the algorithm by using it to predict structures for several small pseudoknotted and non-pseudoknotted RNAs. Although the time and memory demands of the algorithm are steep, we believe this is the first algorithm to be able to fold optimal (minimum energy) pseudoknotted RNAs with the accepted RNA thermodynamic model.

Cited by 16Open access

Tracking accuracy analysis of dynamic programming track before detect algorithm

Shuai Yue, Lingjiang Kong, Jianyu Yang et al. · 2010

Dynamic programming algorithm is an effective track before detect method. It recovers target trajectory at the same time as the detection is declared after processing several successive frames of measurement. This paper simulates the tracking accuracy of each frame of trajectory which is recovered from the maximum of merit function after executing dynamic programming. Several useful results for improving tracking performance are obtained. First the tracking accuracy of middle frames is higher than both sides. Second the lager SNR and the more possible transition states, the more gentle the curves. Third under the condition of large SNR the more possible transition states, the higher accuracy.

Cited by 2

A Faster Dynamic Programming Algorithm For Exact Rectilinear Steiner Trees

JW Lavinus, JP Cohoon · Libra · 1993

An exact rectilinear Steiner minimal tree algorithm is presented that improves upon the time and space complexity of previous guarantees and is easy to implement. Experimental evidence is presented that demonstrates that the algorithm also works well an practice. -T- Note: Abstract extracted from PDF text

Cited by 0Open access

An Efficient Impulsive Adaptive Dynamic Programming Algorithm for Stochastic Systems

Mingming Liang, Yonghua Wang, Derong Liu · IEEE Transactions on Cybernetics · 2022

In this study, a novel general impulsive transition matrix is defined, which can reveal the transition dynamics and probability distribution evolution patterns for all system states between two impulsive "events," instead of two regular time indexes. Based on this general matrix, the policy iteration-based impulsive adaptive dynamic programming (IADP) algorithm along with its variant, which is a more efficient IADP (EIADP) algorithm, are developed in order to solve the optimal impulsive control problems of discrete stochastic systems. Through analyzing the monotonicity, stability, and convergency properties of the obtained iterative value functions and control laws, it is proved that the IADP and EIADP algorithms both converge to the optimal impulsive performance index function. By dividing the whole impulsive policy into smaller pieces, the proposed EIADP algorithm updates the iterative policies in a "piece-by-piece" manner according to the actual hardware constraints. This feature of the EIADP method enables these ADP-based algorithms to be fully optimized to run on all "sizes" of computing devices including the ones with low memory spaces. A simulation experiment is conducted to validate the effectiveness of the present methods.

Cited by 16Open access

Asynchronous stochastic dual dynamic programming algorithm applied to hydrothermal coordination

Felipe Dias de Rezende · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2020

Optimizing power generation planning is very important to achieve the lowest possible costs while keeping an adequate trade-off with electrical network security. High computational resources are required to solve this problem, which is a multistage, stochastic, complex and large scale problem. In some cases, the use of parallel schemes becomes mandatory. A widely used method to solve long-term energy planning problems is an extension of Dual Dynamic Programming (DDP) called Stochastic Dual Dynamic Programming (SDDP) which makes use of sampling techniques to be able to deal with high-dimensional state-spaces. In this work we propose an asynchronous SDDP parallel scheme capable of overcoming the intrinsic synchronism of the traditional parallel version of the SDDP method, thus allowing to better exploit the parallel resources and decrease the overall CPU time to solve the problem. Consistency and performance tests were applied to evaluate the proposed asynchronous SDDP approach and one variant of this algorithm in a problem equivalent to the real Brazilian system, where was verified advantages over using the traditional parallel schema.

Cited by 0Open access

Transmission Range Adjustment in WSNs Based on Dynamic Programming Algorithm

Erdun Zhao, Baolin Yi, Huayang Li et al. · 2006

Recent studies show much energy can be saved and the capacity of wireless sensor networks (WSNs) can be significantly increased when route nodes can have variable transmission ranges. However, this will result some problems difficult to be dealt with. It is well known that in WSNs, energy can be saved by setting the redundancy nodes in sleeping mode along the multi-hop routes. In this paper, we consider the energy efficient route schemes in a linear network with the sensors uniformly distributed and the candidate route nodes randomly deployed. To find an optimal energy efficient route, a dynamic programming algorithm (DPA) is presented to select the optimal route nodes and their transmission ranges. Simulation results show the efficiency of the algorithm

Cited by 5

A ray space interpolation algorithm based on improved dynamic programming

Yang Run-ping · 2010

The ray space interpolation is of crucial importance for Free Viewpoint Television (FTV) and it is a key technique to realize the system of FTV. Nowadays, there are two main methods in the ray space interpolation technique. They are ray space slice interpolation and image domain interpolation. This work mainly concentrates on the later. Firstly, this paper introduces the typical image domain interpolation methods, such as PMI, BMI and DDFI. Then an novel ray space interpolation method is proposed based on the Improved Dynamic Programming(IDP). Finally, the performance of our method is tested on Xmas sequence and experimental results indicate that the IDPI method performs better than traditional methods in image quality and interpolation speed.

Cited by 1

Multi UAV Cooperative Reconnaissance based on Dynamic Programming VDN Algorithm

Jingyi Huang, Ziyi Yang, Jiarui Li et al. · Journal of Intelligent Communication · 2024

This paper proposes a multi agent value decomposition network (VDN) based multi UAV collaborative reconnaissance and control method to address the issue of insufficient strategies for multi UAV collaborative reconnaissance and control. By designing corresponding algorithm networks and training processes, the goal of autonomy, collaboration, and intelligence among multiple unmanned aerial vehicle systems has been achieved, assisting unmanned aerial vehicle combat forces in achieving collaborative operations and decision-making. This article uses AirSim as the simulation verification environment to verify the effectiveness of the proposed algorithm. The experimental results show that the algorithm proposed in this paper can achieve multi UAV collaborative reconnaissance tasks in complex environments, providing an intelligent solution for UAV collaborative control.

Cited by 0Open access

Quantum Algorithm for Dynamic Programming Approach for DAGs and Applications

Kamil Khadiev, Liliya R. Safina · arXiv (Cornell University) · 2022

In this paper, we present a quantum algorithm for the dynamic programming approach for problems on directed acyclic graphs (DAGs). The running time of the algorithm is $O(\sqrt{\hat{n}m}\log \hat{n})$, and the running time of the best known deterministic algorithm is $O(n+m)$, where $n$ is the number of vertices, $\hat{n}$ is the number of vertices with at least one outgoing edge; $m$ is the number of edges. We show that we can solve problems that use OR, AND, NAND, MAX, and MIN functions as the main transition steps. The approach is useful for a couple of problems. One of them is computing a Boolean formula that is represented by Zhegalkin polynomial, a Boolean circuit with shared input and non-constant depth evaluation. Another two are the single source longest paths search for weighted DAGs and the diameter search problem for unweighted DAGs.

Cited by 0Open access

A heuristic dynamic-programming algorithm for 2D unconstrained guillotine cutting

Song X(宋翔), Chu CB(储诚斌), Nie YY(聂义勇) · SIA OpenIR (Chinese Academy of Sciences) · 2004

In this paper, a heuristic dynamic-programming recursion is proposed for solving unconstrained 2D knapsack problem efficiently. The algorithm we propose is an incompletely enumerative method, in which some intricate cutting patterns may not be enumerated. Compared with the traditional dynamic-programming, the algorithm gives a high percentage of optimal solutions (93%) with a much lowered computational complexity. Some theoretical analyses for the algorithm are performed. Computational results are given for small and medium-sized problems.

Cited by 0

Application of Dynamic Programming Algorithm in the Shortest Path Problem

<p>Weiqing Wan<sup>1</sup>, Yuanci Wan<sup>2</sup></p> · Academic Journal of Computing & Information Science · 2024

This paper delves into the specific application of dynamic programming algorithms in solving the shortest path problem in multi-stage graphs. Faced with a given multi-stage graph structure, we are committed to finding an optimal path from vertex 0 to vertex 9, with the aim of minimizing the total length of the pipeline laid, which represents a classic optimization problem. To efficiently and accurately address this challenge, we have chosen dynamic programming as our core tool. This algorithm constructs solutions step-by-step and leverages the results of already solved sub problems to avoid redundant calculations, thereby significantly enhancing computational efficiency. The paper not only elaborates on the fundamental principles of dynamic programming and its application in the shortest path problem within multi-stage graphs, but also provides specific algorithm implementation code in C++ programming language. Our goal is to offer readers a comprehensive and in-depth guide, enabling them to understand and apply dynamic programming algorithms to successfully solve similar optimization problems related to the shortest path in multi-stage graphs.

Cited by 0Open access

A Two-Phase Dynamic Programming Algorithm Tool for DNA Sequences

Oyelade, O. J., Fatumo, S. · Covenant University Repository (Covenant University) · 2013

Sequence alignment has to do with the arrangement of DNA, RNA, and protein sequences to identify areas of similarity. Technic ally, it involves the arrangement of the primary sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Similarity may be a consequence of functional, s tructural, or evolutionary relationships between the sequences. If two sequences in an alignment share a common ancestor, mismatches can be interpreted as mutations, and gaps as insertions. Such information becomes of great use in vital areas such as the study of d iseases, genomics and generally in the biological sciences. Thus, sequence alignment presents not just an exciting field of study, but a field of great importance to mankind. In this light, we extensively studied about seventy (70) existing sequence alignment tools available to us. Most of these tools are not user friendly and cannot be used by biologists. The few tools that attempted both Local and Global algorithms are not ready available freely. We therefore implemented a sequence alignment tool (CU-Aligner) in an understandable, user-friendly and portable way, with click-of-a-button simplicity. This is done utilizing the Needleman-Wunsh and Smith-Waterman algorithms for global and local alignments, respectively which focuses primarily on DNA sequences. Our aligner is implemented in the Java language in both application and applet mode and has been efficient on all windows operating systems.

Cited by 0